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#!/usr/bin/env python
'''
Simple "Square Detector" program.
Loads several images sequentially and tries to find squares in each image.
'''
# Python 2/3 compatibility
from __future__ import print_function
import sys
PY3 = sys.version_info[0] == 3
if PY3:
xrange = range
import numpy as np
import cv2 as cv
def angle_cos(p0, p1, p2):
d1, d2 = (p0-p1).astype('float'), (p2-p1).astype('float')
return abs( np.dot(d1, d2) / np.sqrt( np.dot(d1, d1)*np.dot(d2, d2) ) )
def find_squares(img):
img = cv.GaussianBlur(img, (5, 5), 0)
squares = []
for gray in cv.split(img):
for thrs in xrange(0, 255, 26):
if thrs == 0:
bin = cv.Canny(gray, 0, 50, apertureSize=5)
bin = cv.dilate(bin, None)
else:
_retval, bin = cv.threshold(gray, thrs, 255, cv.THRESH_BINARY)
contours, _hierarchy = cv.findContours(bin, cv.RETR_LIST, cv.CHAIN_APPROX_SIMPLE)
for cnt in contours:
cnt_len = cv.arcLength(cnt, True)
cnt = cv.approxPolyDP(cnt, 0.02*cnt_len, True)
if len(cnt) == 4 and cv.contourArea(cnt) > 1000 and cv.isContourConvex(cnt):
cnt = cnt.reshape(-1, 2)
max_cos = np.max([angle_cos( cnt[i], cnt[(i+1) % 4], cnt[(i+2) % 4] ) for i in xrange(4)])
if max_cos < 0.1:
squares.append(cnt)
return squares
def main():
from glob import glob
for fn in glob('../data/pic*.png'):
img = cv.imread(fn)
squares = find_squares(img)
cv.drawContours( img, squares, -1, (0, 255, 0), 3 )
cv.imshow('squares', img)
ch = cv.waitKey()
if ch == 27:
break
print('Done')
if __name__ == '__main__':
print(__doc__)
main()
cv.destroyAllWindows()
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